Recently, I've seen many people discussing automated trading, and I think this topic is worth a deep dive. To be honest, emotions are the biggest enemies in trading—FOMO, greed, fear—all of which can lead to poor decision-making. Algo trading was created to solve this problem.

What is algo trading? Simply put, it’s using computer programs to automatically execute buy and sell orders. The program analyzes market data based on your set rules and conditions, then places orders automatically. The benefits of doing this are obvious: significantly increased trading efficiency and the complete elimination of emotional bias.

In fact, the operation process of algo trading isn't complicated. First, you need to determine a trading strategy, such as buying when the price drops 5% and selling when it rises 5%. Then, you code this strategy into a language that the computer can understand, with Python being the most commonly used choice. The next critical step is backtesting. Simulating your strategy's past performance using historical data helps you optimize the strategy and improve success rates.

Once the strategy passes testing, you can connect it to a trading platform to start live trading. The program continuously monitors the market, executing trades immediately when conditions are met. This millisecond-level response speed is something human traders simply cannot achieve. After going live, ongoing monitoring is necessary, and parameters should be adjusted based on market changes—this process is very important.

In specific algo trading strategies, I’ve noticed several common approaches. VWAP (Volume Weighted Average Price) is suitable for traders who want to approximate the market average cost; it breaks large orders into smaller ones and executes them gradually. TWAP (Time Weighted Average Price) disperses execution evenly over time, ignoring volume factors. There's also the POV (Percentage of Volume) strategy, which executes trades based on a certain percentage of the total market volume, minimizing market impact.

The advantages of algo trading I mentioned earlier—efficiency and emotional isolation. But there are also clear disadvantages in reality. First, the technical barrier: you need to understand programming and financial markets, which can be difficult for many people. Second, system risks: software bugs, network failures, hardware issues—all of which can lead to significant losses.

Overall, algo trading is a powerful tool, but not a panacea. It can help automate strategy execution and eliminate emotional interference, but only if your strategy is effective and the system is well-managed. If you're interested in this area, you can start with small-scale backtesting to gradually gain experience.